考虑能耗与负载因素的抓取机械臂运动轨迹规划算法

doi:10.13229/j.cnki.jdxbgxb.20230031

摘要/Abstract

摘要：

针对抓取机械臂运动轨迹规划不合理导致的运动路程增加及能耗加剧问题，提出了考虑能耗与负载因素的抓取机械臂运动轨迹规划算法。根据运动学原理建立抓取机械臂运动学模型，通过齐次变换矩阵求解各环节空间位置、姿态，利用时间间隔序列、三次非均匀B样条插值算法约束各个关节角度、速度及其加速度，使其运动轨迹能耗、负载最优；采用线性回归分析方程生成新的群体，找出该群体最优粒子并将其替换原群体中任意一个粒子，反复该过程，即可找出群体最优运动轨迹。实验结果表明，本文算法收敛速度快，且运动轨迹能耗最低。

关键词: 能耗计算, 负载平衡, 抓取机械臂, 运动轨迹, 运动学, 混沌群体, 粒子群算法

Abstract:

Because the trajectory planning of the grasping manipulator is unreasonable， the movement distance is increased， and a large amount of energy is lost. Therefore， an algorithm for trajectory planning of the grasping manipulator considering energy consumption and load factors is proposed. The kinematics model of the grasping manipulator is established according to the kinematics principle. The space position and attitude of each link are solved through homogeneous transformation matrix. The time interval sequence and cubic non-uniform B-spline interpolation algorithm are used to constrain the angle， velocity and acceleration of each joint， so as to optimize the energy consumption and load of its motion trajectory. The linear regression analysis equation is used to generate a new population， find out the optimal particle of the population and replace it with any particle in the original population， and the optimal movement trajectory of the population was found by repeating the process. Experimental results show that the proposed algorithm has fast convergence speed and minimum energy consumption.

Key words: energy consumption calculation, load balancing, grasping manipulator, motion track, kinematics, chaotic population, particle swarm optimization

中图分类号:

TH16

汤小红,龚永健. 考虑能耗与负载因素的抓取机械臂运动轨迹规划算法[J]. 吉林大学学报(工学版), 2024, 54(7): 1862-1868.

Xiao-hong TANG,Yong-jian GONG. Trajectory planning algorithm for grasping manipulator considering energy consumption and load factors[J]. Journal of Jilin University(Engineering and Technology Edition), 2024, 54(7): 1862-1868.

图/表 7

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杆序号	连杆角度/（°）	连杆长度	连杆偏距	关节角旋转范围/（°）
1	0	0	0	±180
2	90	30	0	±90
3	0	70	0	±150
4	0	70	0	±150
5	-90	30	40	±150
6	90	0	0	±180

关节序号	本文算法	文献［4］算法	文献［5］算法
1	20876J	22816J	22163J
2	19356J	20921J	20671J
3	20135J	21085J	20517J
4	17834J	19547J	18951J
5	19832J	20849J	20812J
6	21094J	22714J	21427J